8,656 research outputs found
MAUS Goes Iterative
In this paper we describe further developments of the MAUS system and announce a free-ware software package that may be downloaded from the ’Bavarian Archive for Speech Signals’ (BAS) web site. The quality of the MAUS output can be considerably improved by using an iterative technique. In this mode MAUS will calculated a first pass through all the target speech material using the standard speaker-independent acoustical models of the target language. Then the segmented and labelled speech data are used to re-estimated
the acoustical models and the MAUS procedure is applied again to the speech data using these speaker-dependent models. The last two steps are repeated iteratively until the segmentation converges. The paper describes the general algorithm, the German benchmark for evaluating the method as well as some experiments on German target speakers
Laying the Foundation for In-car Alcohol Detection by Speech
The fact that an increasing number of functions in the automobile are and will be controlled by speech of the driver rises the question whether this speech input may be used to detect a possible alcoholic intoxication of the driver. For that matter a large part of the new Alcohol Language Corpus (ALC) edited by the Bavarian Archive of Speech Signals (BAS) will be used for a broad statistical investigation of possible feature candidates for classification. In this contribution we present the motivation and the design of the ALC corpus as well as first results from fundamental
frequency and rhythm analysis. Our analysis by comparing
sober and alcoholized speech of the same individuals suggests that there are in fact promising features that can automatically be derived from the speech signal during the speech recognition process and will indicate intoxication for most speakers
Matched filter for multi-transducers resonant GW antennas
We analyze two kinds of matched filters for data output of a spherical
resonant GW detector. In order to filter the data of a real sphere, a strategy
is proposed, firstly using an omnidirectional in-line filter, which is supposed
to select periodograms with excitations, secondly by performing a directional
filter on such selected periodograms, finding the wave arrival time, direction
and polarization. We point out that, as the analytical simplifications
occurring in the ideal 6 transducers TIGA sphere do not hold for a real sphere,
using a 5 transducers configuration could be a more convenient choice.Comment: 15 pages and 4 figures, version accepted for publication in PR
On a variant of Giuga numbers
In this paper, we characterize the odd positive integers satisfying the
congruence . We show that
the set of such positive integers has an asymptotic density which turns out to
be slightly larger than 3/8.Comment: 14 page
Analysing Timelines of National Histories across Wikipedia Editions: A Comparative Computational Approach
Portrayals of history are never complete, and each description inherently
exhibits a specific viewpoint and emphasis. In this paper, we aim to
automatically identify such differences by computing timelines and detecting
temporal focal points of written history across languages on Wikipedia. In
particular, we study articles related to the history of all UN member states
and compare them in 30 language editions. We develop a computational approach
that allows to identify focal points quantitatively, and find that Wikipedia
narratives about national histories (i) are skewed towards more recent events
(recency bias) and (ii) are distributed unevenly across the continents with
significant focus on the history of European countries (Eurocentric bias). We
also establish that national historical timelines vary across language
editions, although average interlingual consensus is rather high. We hope that
this paper provides a starting point for a broader computational analysis of
written history on Wikipedia and elsewhere
Semantic Processing of Out-Of-Vocabulary Words in a Spoken Dialogue System
One of the most important causes of failure in spoken dialogue systems is
usually neglected: the problem of words that are not covered by the system's
vocabulary (out-of-vocabulary or OOV words). In this paper a methodology is
described for the detection, classification and processing of OOV words in an
automatic train timetable information system. The various extensions that had
to be effected on the different modules of the system are reported, resulting
in the design of appropriate dialogue strategies, as are encouraging evaluation
results on the new versions of the word recogniser and the linguistic
processor.Comment: 4 pages, 2 eps figures, requires LaTeX2e, uses eurospeech.sty and
epsfi
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